PrivCode++ introduces the first DP code generation method protecting both prompts and code via latent-conditioned two-stage training, claiming higher utility and stronger privacy than prior baselines.
arXiv preprint arXiv:2402.08699 , year=
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
VERIMED translates natural-language requirements to formal logic via LLMs, detects ambiguity from stochastic formalization differences, and audits for inconsistency and safety violations using SMT queries.
citing papers explorer
-
PrivCode++: Latent-Conditioned Differentially Private Code Generation for Comprehensive Guarantees
PrivCode++ introduces the first DP code generation method protecting both prompts and code via latent-conditioned two-stage training, claiming higher utility and stronger privacy than prior baselines.
-
Neurosymbolic Auditing of Natural-Language Software Requirements
VERIMED translates natural-language requirements to formal logic via LLMs, detects ambiguity from stochastic formalization differences, and audits for inconsistency and safety violations using SMT queries.